拟南芥表皮毛发育的分子机制

拟南芥（Arabidopsis thaliana）表皮毛是存在于地上部分表皮组织的一种特化的、典型的单细胞结构。近几年,对其发育的分子调控机制的研究取得了很大进展,已克隆出大量的控制表皮毛不同发育阶段的基因,通过对这些基因的功能解析揭示出表皮毛发育及生长调节的内在分子机制。该文对拟南芥表皮毛发育的最新研究进展进行综述,并展望了关于表皮毛的研究方向及潜在的应用价值。     

拟南芥表皮毛发育的分子机制

拟南芥(Arabidopsis thaliana)表皮毛是存在于地上部分表皮组织的一种特化的、典型的单细胞结构。近几年, 对其发育的分子调控机制的研究取得了很大进展, 已克隆出大量的控制表皮毛不同发育阶段的基因, 通过对这些基因的功能解析揭示出表皮毛发育及生长调节的内在分子机制。该文对拟南芥表皮毛发育的最新研究进展进行综述, 并展望了关于表皮毛的研究方向及潜在的应用价值。     

拟南芥根系发育的分子机制研究进展

拟南芥初生根和次生根的发育受不同遗传通路所调控,其中内源激素途径尤其是生长素途径在拟南芥主根、侧根以及根毛的发育过程中均发挥着重要作用.同时也存在一些不依赖于激素通路的遗传途径,如UPB1能通过调节根尖分生区和伸长区活性氧种类的平衡来调控根系顶端分生组织活性,进而影响根系的生长.本文对近年来国内外有关模式植物拟南芥根系发育的分子机制研究进展分别从初生根发育、侧根发育和根毛发育3个方面进行综述.     

拟南芥和琴叶拟南芥中MADS-box基因的比较进化分析

MADS-box基因编码一类转录因子。在被子植物中,MADS-box基因对于营养生长和生殖发育都有重要的调控作用,是植物体(特别是花序、花和果实)的正常发育所不可或缺的。为了理解近缘物种在遗传基础上的异同,我们对拟南芥(Arabidopsis thaliana)和琴叶拟南芥(A.lyrata)基因组中MADS-box基因的拷贝数目和进化式样进行了比较分析。通过搜索公共数据库,我们在拟南芥和琴叶拟南芥中分别鉴定出了106和115个基因。系统发育分析的结果表明,这些基因属于I型和II型MADS-box基因。在两个物种分化之后,II型基因的拷贝数目变化不大,I型基因则经历了多次独立的基因丢失和获得事件。通过比较这些基因在染色体上的排列,我们不但鉴定出了存在微共线性的基因组区段,而且发现新基因产生的主要机制是串联重复和散在重复。分子进化的研究进一步表明,I型和II型基因在进化式样上存在着显著差异:II型基因在进化中一般都受到了较强的选择压力,而I型基因大多受到的选择压力较弱。本研究将为深入理解近缘物种在基因和基因组层面上的异同、探讨物种分化和生物多样性形成的机制等问题提供新思路。     

MADS-box转录因子的相互作用及对果实发育和成熟的调控

MADS-box基因编码的蛋白是一类数目庞大的转录因子家族, 通过与其他转录因子相互作用形成同源或异源二聚体, 调控着整个植株的生长发育。文章对近年来MADS-box转录因子的相互作用及对果实发育和成熟的调控作用的研究进展进行了综述, 为了解MADS-box转录因子的作用方式和作用机理及深入研究MADS-box基因对调控果实发育和成熟的作用提供参考。     

冷胁迫条件下拟南芥Rubisco相互作用蛋白质的比较分析

1,5-二磷酸核酮糖羧化酶/加氧酶(Rubisco,EC 4.1.1.39)在生物适应环境变化的过程中起到重要的作用.位于叶绿体中与冷胁迫密切相关的非常重要的复合酶——Rubisco,其相互作用的蛋白质至今没有系统的研究.对拟南芥进行4种处理:a.持续在20℃生长(对照);b.4℃4 h冷胁迫;c.4℃24 h冷胁迫;d.4℃24 h冷胁迫后放入20℃恢复24 h.然后利用免疫共沉淀、十二烷基硫酸钠聚丙烯酰胺凝胶电泳及基质辅助激光解析电离飞行时间质谱技术,在冷胁迫条件下研究了拟南芥光合抑制与Rubisco相互作用蛋白质解聚之间的关系.在鉴定出的5个与冷胁迫相关的Rubisco相互作用蛋白质中,AAA-型ATP酶家族蛋白和糖基转移酶对Rubisco活性及植物适应冷胁迫起着重要的作用.研究结果表明,Rubisco复合酶体系的解聚可能是低温胁迫下拟南芥光合速率降低的主要原因.     

蛋白质相互作用网络进化分析研究进展

近年来,随着高通量实验技术的发展和广泛应用,越来越多可利用的蛋白质相互作用网络数据开始出现．这些数据为进化研究提供了新的视角．从蛋白质、蛋白质相互作用、模体、模块直到整个网络五个层次,综述了近年来蛋白质相互作用网络进化研究领域的主要进展,侧重于探讨蛋白质相互作用、模体、模块直到整个网络对蛋白质进化的约束作用,以及蛋白质相互作用网络不同于随机网络特性的起源和进化等问题．总结了前人工作给学术界的启示,探讨了该领域未来可能的发展方向．     

基于相互作用的蛋白质功能预测

蛋白质功能预测是后基因时代研究的热点问题。基于相互作用的蛋白质功能预测方法目前应用比较广泛,但是当"伙伴蛋白质"(interacting partners)数目k较小时,其预测准确率不高。从蛋白质相互作用网络入手,结合"小世界网络"特性,有效解决了k较小时预测准确率不高的问题。对酵母(Saccharomyces cerevisiae)蛋白质的相互作用网络进行预测,当k≤4时其预测准确率比相同条件下的GO(global optimization)方法有一定提高。实验结果表明:该方法能够有效的应用于伙伴蛋白质数目较小时的蛋白质功能预测。     

基于贝叶斯网络和相互作用可信度的蛋白质功能预测方法

蛋白质功能注释是后基因组时代研究的核心内容之一,基于蛋白质相互作用网络的蛋白质功能预测方法越来越受到研究者们的关注.提出了一种基于贝叶斯网络和蛋白质相互作用可信度的蛋白质功能预测方法.该方法在功能预测过程中为待注释的蛋白质建立贝叶斯网络预测模型,并充分考虑了蛋白质相互作用的可信度问题.在构建的芽殖酵母数据集上的三重交叉验证测试表明,在功能预测过程中考虑蛋白质可信度能够有效地提高功能预测的性能.与现有一些算法相比,该方法能够给出令人满意的预测效果.     

隐花色素与COP1在拟南芥光控发育中相互作用的直接证据

光敏色素和隐花色素控制着拟南芥在黑暗条件下的暗形态建成和光环境下的光形态建成。ＣＯＰ1是光控发育的抑制因子。它在黑暗中与ＨＹ5结合 ,通过 2 6Ｓ蛋白体使ＨＹ5降解。但目前对于光受体如何调节ＣＯＰ1还知之甚少。将含有隐花色素 1 (ＣＲＹ1 )Ｃ端 4 90＿681的片段 (ＣＣＴ1 )和隐花色素 2 (ＣＲＹ2 )Ｃ端 4 86＿61 2的片段 (ＣＣＴ2 ) ,以及ＧＵＳ＿ＣＣＴ1和ＧＵＳ＿ＣＣＴ2亚克隆到酵母双杂交载体上 ,载体具有ＬｅｘＡＤＮＡ结合区域和ＧＡＬ4活化区域 (ＡＤ)。实验表明 ,ＬｅｘＡ＿ＣＣＴ2和ＬｅｘＡ＿ＧＵＳ＿ＣＣＴ2与ＡＤ＿Ｃ…     

Predicting Disease-Related Proteins Based on Clique Backbone in Protein-Protein Interaction Network

Network biology integrates different kinds of data, including physical or functional networks and disease gene sets, to interpret human disease. A clique (maximal complete subgraph) in a protein-protein interaction network is a topological module and possesses inherently biological significance. A disease-related clique possibly associates with complex diseases. Fully identifying disease components in a clique is conductive to uncovering disease mechanisms. This paper proposes an approach of predicting disease proteins based on cliques in a protein-protein interaction network. To tolerate false positive and negative interactions in protein networks, extending cliques and scoring predicted disease proteins with gene ontology terms are introduced to the clique-based method. Precisions of predicted disease proteins are verified by disease phenotypes and steadily keep to more than 95%. The predicted disease proteins associated with cliques can partly complement mapping between genotype and phenotype, and provide clues for understanding the pathogenesis of serious diseases.     

Protein Interaction Network of Arabidopsis thaliana Female Gametophyte Development Identifies Novel Proteins and Relations

Although the female gametophyte in angiosperms consists of just seven cells, it has a complex biological network. In this study, female gametophyte microarray data from Arabidopsis thaliana were integrated into the Arabidopsis interactome database to generate a putative interaction map of the female gametophyte development including proteome map based on biological processes and molecular functions of proteins. Biological and functional groups as well as topological characteristics of the network were investigated by analyzing phytohormones, plant defense, cell death, transporters, regulatory factors, and hydrolases. This approach led to the prediction of critical members and bottlenecks of the network. Seventy-four and 24 upregulated genes as well as 171 and 3 downregulated genes were identified in subtracted networks based on biological processes and molecular function respectively, including novel genes such as the pathogenesis-related protein 4, ER type Ca²⁺ ATPase 3, dihydroflavonol reductase, and ATP disulfate isomerase. Biologically important relationships between genes, critical nodes, and new essential proteins such as AT1G26830, AT5G20850, CYP74A, AT1G42396, PR4 and MEA were found in the interactome''s network. The positions of novel genes, both upregulated and downregulated, and their relationships with biological pathways, in particular phytohormones, were highlighted in this study.     

Interaction between Intrinsically Disordered Proteins Frequently Occurs in a Human Protein-Protein Interaction Network

Intrinsic protein disorder is a widespread phenomenon characterised by a lack of stable three-dimensional structures and is considered to play an important role in protein-protein interactions (PPIs). This study examined the genome-wide preference of disorder in PPIs by using exhaustive disorder prediction in human PPIs. We categorised the PPIs into three types (interaction between disordered proteins, interaction between structured proteins, and interaction between a disordered protein and a structured protein) with regard to the flexibility of molecular recognition and compared these three interaction types in an existing human PPI network with those in a randomised network. Although the structured regions were expected to become the identifiers for binding recognition, this comparative analysis revealed unexpected results. The occurrence of interactions between disordered proteins was significantly frequent, and that between a disordered protein and a structured protein was significantly infrequent. We found that this propensity was much stronger in interactions between nonhub proteins. We also analysed the interaction types from a functional standpoint by using GO, which revealed that the interaction between disordered proteins frequently occurred in cellular processes, regulation, and metabolic processes. The number of interactions, especially in metabolic processes between disordered proteins, was 1.8 times as large as that in the randomised network. Another analysis conducted by using KEGG pathways provided results where several signaling pathways and disease-related pathways included many interactions between disordered proteins. All of these analyses suggest that human PPIs preferably occur between disordered proteins and that the flexibility of the interacting protein pairs may play an important role in human PPI networks.     

Identification of Essential Proteins Based on Ranking Edge-Weights in Protein-Protein Interaction Networks

Essential proteins are those that are indispensable to cellular survival and development. Existing methods for essential protein identification generally rely on knock-out experiments and/or the relative density of their interactions (edges) with other proteins in a Protein-Protein Interaction (PPI) network. Here, we present a computational method, called EW, to first rank protein-protein interactions in terms of their Edge Weights, and then identify sub-PPI-networks consisting of only the highly-ranked edges and predict their proteins as essential proteins. We have applied this method to publicly-available PPI data on Saccharomyces cerevisiae (Yeast) and Escherichia coli (E. coli) for essential protein identification, and demonstrated that EW achieves better performance than the state-of-the-art methods in terms of the precision-recall and Jackknife measures. The highly-ranked protein-protein interactions by our prediction tend to be biologically significant in both the Yeast and E. coli PPI networks. Further analyses on systematically perturbed Yeast and E. coli PPI networks through randomly deleting edges demonstrate that the proposed method is robust and the top-ranked edges tend to be more associated with known essential proteins than the lowly-ranked edges.     

Two Related RNA-editing Proteins Target the Same Sites in Mitochondria of Arabidopsis thaliana

The facilitators for specific cytosine-to-uridine RNA-editing events in plant mitochondria and plastids are pentatricopeptide repeat (PPR)-containing proteins with specific additional C-terminal domains. Here we report the related PPR proteins mitochondrial editing factor 8 (MEF8) and MEF8S with only five such repeats each to be both involved in RNA editing at the same two sites in mitochondria of Arabidopsis thaliana. Mutants of MEF8 show diminished editing in leaves but not in pollen, whereas mutants of the related protein MEF8S show reduced RNA editing in pollen but not in leaves. Overexpressed MEF8 or MEF8S both increase editing at the two target sites in a mef8 mutant. Double mutants of MEF8 and MEF8S are not viable although both identified target sites are in mRNAs for nonessential proteins. This suggests that MEF8 and MEF8S may have other essential functions beyond these two editing sites in complex I mRNAs.     

Correction to: Transient Sub-cellular Localization and In Vivo Protein-Protein Interaction Study of Multiple Abiotic Stress Responsive AteIF4A-III and AtALY4 Proteins in Arabidopsis thaliana

Plant Molecular Biology Reporter - The affiliation 2 in the published article was Academy of Scientific and Innovative Research (AcSIR), CSIR-NEIST Campus, Jorhat, Assam 785,006, India.     

拟南芥COPT家族蛋白研究进展

铜(Cu)是植物必需的微量元素, 作为多种酶的辅因子参与许多植物生理生化反应。Cu缺乏和过量均影响植物正常生长发育, 因此植物进化出精妙复杂的调控网络来严格控制植物体内的Cu含量。植物Cu转运蛋白COPT家族成员与Cu有很高的亲和力, 能够调节植物对Cu的吸收和转运, 在维持植物体内Cu稳态平衡过程中发挥重要作用。COPT蛋白涉及不同的Cu转运功能, 如从外界环境中摄取Cu、从细胞器中输出Cu、长距离运输Cu以及在不同器官间动用和再分配Cu。此外, COPT蛋白在其它离子的稳态平衡维持、昼夜节律性生物钟调控、植物激素合成和植物对激素信号的感受过程中也发挥重要作用。该文综述了模式植物拟南芥(Arabidopsis thaliana) COPT家族各成员的表达和定位、调控机制以及生物学功能等方面的最新进展。     

拟南芥COPT家族蛋白研究进展

铜(Cu)是植物必需的微量元素, 作为多种酶的辅因子参与许多植物生理生化反应。Cu缺乏和过量均影响植物正常生长发育, 因此植物进化出精妙复杂的调控网络来严格控制植物体内的Cu含量。植物Cu转运蛋白COPT家族成员与Cu有很高的亲和力, 能够调节植物对Cu的吸收和转运, 在维持植物体内Cu稳态平衡过程中发挥重要作用。COPT蛋白涉及不同的Cu转运功能, 如从外界环境中摄取Cu、从细胞器中输出Cu、长距离运输Cu以及在不同器官间动用和再分配Cu。此外, COPT蛋白在其它离子的稳态平衡维持、昼夜节律性生物钟调控、植物激素合成和植物对激素信号的感受过程中也发挥重要作用。该文综述了模式植物拟南芥(Arabidopsis thaliana) COPT家族各成员的表达和定位、调控机制以及生物学功能等方面的最新进展。